Attila Kohut

A three-dimensional (3D) Au nanoparticles (AuNPs)-cellulose interface was engineered via solvent-free spark ablation and direct particle deposition onto filter paper, forming a percolated junction network with abundant nanoscale gaps that enables surface-enhanced Raman scattering signal amplification under a fiber-optic probe geometry. The resulting 3D plasmonic network exhibits good signal reproducibility, as verified by Rhodamine 6G mapping (RSD 13.5–16.6%). Using thiabendazole (TBZ) as a representative small-molecule residue, the platform enables quantitative detection down to 0.08 ppm in methanol and 0.10 ppm in untreated apple juice, supporting residue monitoring in real matrices. A nonlinear logarithmic calibration model captures the concentration-dependent response without requiring complex chemometric processing. TBZ-spiked apple juice samples showed satisfactory recoveries of ca. 83–105%, while selectivity against thiram, batch-to-batch repeatability, and intra-/inter-day precision further confirm the analytical robustness of the engineered interface. Overall, the AuNP-cellulose junction network couples interface-driven signal amplification with point-of-need applicability, advancing flexible Raman-based sensing for rapid residue screening in food safety and related chemical/biosensing scenarios. Graphical Abstract

This study presents a combined experimental and numerical approach for investigating nanoparticle (NP) transport in a spark discharge generator (SDG), with particular emphasis on the determination of particle residence time (RT). A tracer-based experimental method is proposed to measure the residence time distribution (RTD) of NPs, incorporating a two-step correction procedure to eliminate delays arising from both the sampling line and the response time of the condensation particle counter (CPC). This methodology enables reliable, time-resolved characterization of particle transport under varying operating conditions.The RT was defined as the mode of the residence time distribution (RTD), and all subsequent analyses were restricted to this characteristic value. The experimentally determined RT values were systematically analysed as a function of volumetric flow rate and spark gap distance, and were directly compared to results obtained from joint computational fluid dynamics (CFD) and particle tracing (PT) simulations. While the simulations accurately reproduced particle transport in the tubes of the sampling line (simple geometry), significant discrepancies were observed when particles were assumed to originate directly from the spark gap, leading to systematic underestimation of the measured RT. By introducing a spatially shifted and broadened particle formation zone in the simulations, a strong agreement between experimental and numerical results was achieved. This finding suggests that NP formation occurs predominantly outside of the discharge region, following the rapid expansion and transport of atomic vapour. The developed methodology thus provides a robust framework for experimentally determining particle RT and, when combined with simulations, enables indirect localization of the particle formation zone. On one hand, this approach offers new insights into the mechanisms governing NP formation and supports the optimization of nano-material synthesis processes in spark ablation systems, on the other.

Time-resolved in-flight analysis reveals the temporal evolution of CuZn nanoparticle composition during spark ablation.

Binary nanoparticles (BNPs), composed of two distinct materials, offer tailored properties advantageous for various applications, including enhanced catalytic, magnetic, and optical behavior. Among the synthesis methods for BNPs, spark ablation stands out for its capability to produce multicomponent nanostructures with tunable compositions. This study investigates the mixing dynamics of material vapors in spark ablation, a critical step in the process of BNP formation. Using spatially and temporally resolved optical emission spectroscopy (OES), we track the expansion and interaction of gold and silver vapors within the spark gap of a spark discharge generator. The collected data reveal the evolution of the vapor mixing process, complemented by a quantitative model that maps the variation of the gold-to-silver concentration ratio over time and space. We correlate these observations with the composition distribution of synthesized AuAg BNPs, as analyzed by scanning transmission electron microscopy (STEM) with energy-dispersive X-ray spectrometry (EDX). Our findings elucidate key factors influencing the compositional variance of BNPs, facilitating the understanding of the role of vapor mixing in achieving well-controlled particle processes via spark ablation.